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Machine Learning Developer Intern Jobs in Waterloo, ON

Linamar

Apprentice - Machinist

Guelph, ON · On-site

Apply knowledge of machine shop theory and procedures, shop mathematics, machine ability of ... Possess drive and motivation to maintain continuous learning from daily work activities What ...

Linamar

Apprentice - Machinist

Guelph, ON

Apply knowledge of machine shop theory and procedures, shop mathematics, machine ability of ... Possess drive and motivation to maintain continuous learning from daily work activities What ...

CSMC

Geophysicist

Waterloo, ON · On-site

Understanding of geostatistics, data analytics, or machine learning applications in geoscience ... You'll join a team of engineers, scientists, and mission‑driven builders who care deeply about ...

Acceldata

Field Engineering Co-Op

Kitchener, ON

CA$20 - CA$30/hr

WHY INTERN WITH US * Gain valuable experience at a fast-growing tech startup in Canada. * Work ... Commit to continuous learning and professional development, adapting to new tools, languages, and ...

Acceldata

Sales Engineering Co-Op

Kitchener, ON

CA$20 - CA$30/hr

WHY INTERN WITH US * Gain valuable experience at a fast-growing tech startup in Canada. * Work on ... Commit to continuous learning and professional development, adapting to new tools, languages, and ...

Magna

Manufacturing Engineering

Milton, ON · On-site

CA$85K - CA$105K/yr

... machine vision, connected equipment and digital manufacturing tools. You will take ideas from ... Curiosity and confidence learning new technology. Experience or exposure to AI and data analytics ...

New

Acceldata

Software Engineering Co-op

Kitchener, ON · On-site

Why Intern With Us: At Acceldata, you won't just be writing code; you'll be shaping the foundation ... Commit to continuous learning and professional development, adapting to new tools, languages, and ...

Manulife

Lead Cybersecurity Architect

Waterloo, ON · Hybrid

Design and implement security frameworks for Machine Learning (ML), Generative AI (GenAI), and ... engineers on threat modelling and secure software development methodologies. * Cloud Security

Dialpad

AI Engineer, Agentic Voice (TTS)

Kitchener, ON · On-site

... parameter machinery, and exposing voice attributes to our customer-facing UI. You'll partner ... Strong Python and hands-on experience with deep learning frameworks (e.g. PyTorch). * Speech ...

Linamar

Automation Technician

Guelph, ON · On-site

... and machinery in conjunction with Engineering and Maintenance. Responsibility * Work with ... Continuous learning to maintain a current knowledge of policies, procedures, and industry standards.

Linamar

Automation Technician

Guelph, ON · On-site

... and machinery in conjunction with Engineering and Maintenance. Responsibility * Work with ... Continuous learning to maintain a current knowledge of policies, procedures, and industry standards.

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All JobsMachine Learning Developer Intern JobsMachine Learning Developer Intern Jobs in Waterloo, ON

Machine Learning Developer Intern information

What does a machine learning developer intern do?

A Machine Learning Developer Intern assists with developing, testing, and implementing machine learning models and algorithms under the guidance of experienced engineers or data scientists. Their tasks may include data preprocessing, model training, evaluating model performance, and helping deploy models into production environments. Interns often collaborate with team members to solve real-world problems using machine learning techniques and may also assist in researching new methodologies or optimizing existing solutions. This role provides hands-on experience in coding, data analysis, and applying theoretical concepts to practical scenarios.

What are the key skills and qualifications needed to thrive as a machine learning developer intern?

To thrive as a Machine Learning Developer Intern, you need a solid understanding of programming (especially Python), statistics, and machine learning concepts, often supported by coursework or relevant project experience. Familiarity with ML frameworks like TensorFlow or PyTorch, and tools such as Jupyter Notebooks and version control systems like Git, is typically expected. Strong analytical thinking, eagerness to learn, and effective communication help interns contribute to team projects and adapt quickly. These skills are essential for solving real-world problems, collaborating with teams, and building a foundation for a successful career in machine learning.

How do machine learning developer interns typically collaborate with data scientists and engineers during their internship?

Machine Learning Developer Interns often work closely with data scientists to understand the problem domain, gather relevant datasets, and select appropriate models. They also collaborate with software engineers to integrate machine learning solutions into existing systems, ensuring scalability and performance. Regular communication through stand-up meetings, code reviews, and collaborative platforms is common, allowing interns to learn best practices and receive feedback on their work. This teamwork not only enhances technical skills but also provides valuable exposure to real-world deployment and project lifecycle management.

What is the difference between Machine Learning Developer Intern vs Data Scientist Intern?

AspectMachine Learning Developer InternData Scientist Intern
Required CredentialsTypically pursuing or recently completed a degree in Computer Science, Data Science, or related fields; knowledge of programming languages like Python or JavaSimilar educational background; strong skills in statistics, programming, and data analysis
Work EnvironmentHands-on experience with ML models, algorithms, and software development in tech or research settingsData analysis, visualization, and interpretation in business or research contexts
Employer & Industry UsageTech companies, startups, research labs focusing on AI/ML projectsBusiness, finance, healthcare, and research organizations analyzing large datasets

Both roles involve working with data and programming, but Machine Learning Developer Interns focus more on building and deploying ML models, while Data Scientist Interns emphasize data analysis and insights. The roles often overlap, especially in tech environments, but their core tasks differ slightly.

What cities near Waterloo, ON are hiring for Machine Learning Developer Intern jobs?

Cities near Waterloo, ON with the most Machine Learning Developer Intern job openings:

Machine Learning Developer Intern jobs near you

Staff Backend Engineer - Search FX (Discovery Experience)

Faire

Kitchener, ON

CA$190K - CA$262K/yr

Full-time

Re-posted 27 days ago

Job description

About the Role:

The Discovery Search team (Search FX) sits at the intersection of search, evaluation, and personalization shaping how retailers find the products they love. Our mission is to build the most intuitive, intelligent, and delightful discovery experience in wholesale: one that feels less like a search engine and more like a trusted merchant with an encyclopedic knowledge of what's in stock and what will sell.

As a Staff Engineer on the Search FX team, you will be a primary technical architect for our retailer-facing search surfaces. You will own the technical roadmap for search, recommendations, and Gen-AI experiences that drive a meaningful share of marketplace engagement. You will bridge the gap between high-scale infrastructure and world-class UX, helping unify retrieval, ranking, and personalization into a cohesive, high-performance system.

You're excited about this role because...
  • You will own the technical vision: Define the end-to-end architecture for Faire's search and discovery experience, ensuring it is fast, relevant, and deeply personalized.
  • You'll build at the AI frontier: Integrate LLM-powered capabilities, such as natural language search and intelligent query understanding, directly into the product.
  • You'll solve complex scale problems: Help build high-scale, low-latency systems that navigate millions of products while meeting strict industry latency benchmarks.
  • You'll drive cross-functional impact: Partner closely with Data Science, Product, and Design to iterate on ranking models and UX components.
  • You'll be a mentor and leader: Foster a culture of engineering excellence and ownership, upskilling the team on technical expertise and decision-making.
What You'll Do:
  • Architect Next-Gen Search: Lead the design of composable grids, intent-aware routing, and orchestration layers that unify retrieval and ranking.
  • Modernize Query Understanding: Leverage LLMs to consolidate the QU stack, improving accuracy for long-tail queries and edge cases.
  • Optimize Performance: Drive initiatives to increase retrieval candidates (e.g., 10x growth) while maintaining stable search latency.
  • Launch AI-Driven Features: Develop systems like "Search Missions" that use offline pipelines and LLMs to recover failed search sessions through expanded queries.
  • Bridge AI and UX: Work with client engineers on SDUI and React Server Components to improve performance and developer velocity for dynamic search layouts.
  • System Ownership: Take accountability for the reliability and observability of the search funnel, from query planner refactors to real-time retrieval monitoring.
Qualifications:
  • Experience: 7+ years of professional software engineering experience, with 3+ years as a technical leader driving complex, cross-team projects.
  • Product Sensibility: A strong user-first mindset and the ability to translate ambiguous business problems into clear technical direction.
  • AI/ML Familiarity: Experience partnering with Data Science to deploy and leverage machine learning and gen-AI systems in search experiences across ranking and retrieval.
  • Domain Expertise: knowledge of search/query processing, including traditional, semantic, and hybrid frameworks (e.g., Elasticsearch, Lucene).
  • Technical Stack: Strong programming skills in Kotlin or Java, with experience in high-performance backend systems, Protocol Buffers, and MySQL.
  • Strategic Leadership: Demonstrated ability to contribute to team strategy without supervision and influence the broader organizational roadmap.
Technologies We Use and Teach:
  • Backend: Kotlin, Java 16, Hibernate, Guice, Jersey
  • Search/Data: Elasticsearch, FAISS, Redis, DynamoDB
  • Communication: Protocol Buffers, HTTP, JSON
  • Infrastructure: AWS, Kubernetes, Buildkite, Datadog
Salary Range:

Canada: the pay range for this role is $190,500 - $262,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

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